Question

我有一张表：

Column1 ||  Column2 || Column3
------------------------

A   ||  01  ||  Test1

A   ||  02  ||  Test2

A   ||  03  ||  Test3

B   ||  04  ||  Test4

C   ||  05  ||  Test5

C   ||  06  ||  Test6

注意：Column2是主键

所需的输出表如下：

Related ||  Column1 ||  Column2 ||  Column3
-------------------------------

**  ||  A   ||  01  ||  Test1

**  ||  A   ||  02  ||  Test2

**  ||  A   ||  03  ||  Test3

    ||  B   ||  04  ||  Test4

**  ||  C   ||  05  ||  Test5

**  ||  C   ||  06  ||  Test6

这里我试图通过创建一个新列来显示column1的所有相关数据和“**”。我已尝试将查询用作：

SELECT kh.Column4,
CASE WHEN COUNT(c.Column1) > 1 THEN '*' ELSE '' END AS Related 
FROM <TableName> WITH(NOLOCK) 
JOIN <TableName2> kh WITH(NOLOCK) ON (kh.Column4 = c.Column1)
GROUP BY Column4

但没有获得所需的输出。还有其他办法吗？

Answer 1

这应该有效：

/*  Setting up the sample data */

    declare @kh table
        (
     Letter nvarchar(1),
     Number int identity(1, 1)
                primary key
                not null,
     Test nvarchar(10)
    )

insert  into @kh
        (Letter)
values  (N'A'),
        (N'A'),
        (N'A'),
        (N'B'),
        (N'C'),
        (N'C')

update  @kh
set     Test = N'Test' + cast(Number as nvarchar)


/* The requested solution using the above sample data */

select  case when h.ColCount > 1 then N'**'
             else N''
        end as Dupes,
        k.Letter,
        k.Number,
        k.Test
from    @kh as k
left join (
           select   kh.Letter,
                    count(1) as ColCount
           from     @kh as kh
           group by kh.Letter
          ) as h
on      k.Letter = h.Letter

Answer 2

在您的方案中，以下代码将起作用。首先，我在内部块中取重复值，并使用实际表左连接以获得结果。

SELECT 
    CASE WHEN REP.Column1 IS NOT NULL THEN '**' ELSE '' END AS Related,
    TT.Column1, TT.Column2, TT.Column3
FROM TestTable TT 
LEFT JOIN (
    SELECT Column1
    FROM TestTable
    GROUP BY Column1
    HAVING COUNT(Column1) > 1
) REP ON REP.Column1 = TT.Column1

工作小提琴：http://sqlfiddle.com/#!3/ffa8b/5

Answer 3

您可以在案例陈述中使用import moduleFoo from './foo'; import moduleBar from './bar'; angular.module('app', [moduleFoo, moduleBar]);函数，而无需分组

COUNT() OVER(PARTITION BY)

关联列数据

3 个答案: